[R] dependent p.values in R

[Fernando Marmolejo Ramos]

dear michael

thanks for your input

i do agree in visual tests (indeed a recent paper in TAS=http://amstat.tandfonline.com/doi/abs/10.1080/00031305.2015.1077728 )

as a matter of fact, the test i'm after is simply for comparative purposes with some visualisation techniques

best

f

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Fernando Marmolejo-Ramos
Postdoctoral Fellow
Gösta Ekman Laboratory
Department of Psychology
Stockholm University
Frescati Hagväg 9A, Stockholm 114 19
Sweden

ph = +46 08-16 46 07
website = http://sites.google.com/site/fernandomarmolejoramos/

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

________________________________________
From: Michael Friendly <friendly at yorku.ca>
Sent: Sunday, 10 July 2016 7:51 PM
To: Fernando Marmolejo Ramos; Marc Girondot; r-help at r-project.org
Subject: Re: dependent p.values in R

Hello Fernando

First, ask yourself what Gosta Ekman would have said if you asked him
this question.  He would have asked "does it make any difference to
your conclusion?"  He might also have asked you "Did you do a visual
test?"  Plot your data as a QQ plot or density plot?

If the test doesn't make a difference in conclusions, it is a waste of
your time (and ours) to worry about how to cite a
'combined p.value' (if such an animal exists), presumably to
more decimal places than is worth worrying about.

If the test *does* make a difference about normality, then ask yourself
does the degree of non-normality impede my substantive conclusions.

HTH,
-ichael

On 7/10/16 3:39 AM, Fernando Marmolejo Ramos wrote:
> hi marc
>
> say i have a vector with some x number of observations
>
> x = c(23, 56, 123, ..... )
>
> and i want to know how normal it is
>
> as there are many normality tests, i want to combine their p.values
>
> so, suppose i use shapiro.wilk, anderson darling and jarque bera and each will give a pvalue
>
> i could simply average those p,values but to my knowledge that approach is biased
>
> so i thought, in the same way there is a method to combine independent pvalues (e.g. stouffer method); is there a way to combine dependent pvalues?
>
> best
>
> f
>
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> Fernando Marmolejo-Ramos
> Postdoctoral Fellow
> Gösta Ekman Laboratory
> Department of Psychology
> Stockholm University
> Frescati Hagväg 9A, Stockholm 114 19
> Sweden
>
> ph = +46 08-16 46 07
> website = http://sites.google.com/site/fernandomarmolejoramos/
>
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>
> ________________________________________
> From: Marc Girondot <marc.girondot at u-psud.fr>
> Sent: Sunday, 10 July 2016 8:25 AM
> To: r-help at r-project.org; Fernando Marmolejo Ramos
> Subject: Re: [R] dependent p.values
>
> Le 09/07/2016 à 17:17, Fernando Marmolejo Ramos a écrit :
>> hi all
>>
>>
>> does any one know a method to combine dependent p.values?
>>
>>
> First, it is a stats question and not a R question. So you could have
> better chance to ask this in stackexchange forum.
> Second, your question is difficult to answer without context: why
> p.values are dependent ? Do they come from the same dataset ? Or are
> they linked by an external source ? For both these situations, combining
> dependent p.values seems strange for me.
> When you will ask question in stackexchange, be more precise.
> Sincerely,
> Marc Girondot
>
> --
> __________________________________________________________
> Marc Girondot, Pr
>
> Laboratoire Ecologie, Systématique et Evolution
> Equipe de Conservation des Populations et des Communautés
> CNRS, AgroParisTech et Université Paris-Sud 11 , UMR 8079
> Bâtiment 362
> 91405 Orsay Cedex, France
>
> Tel:  33 1 (0)1.69.15.72.30   Fax: 33 1 (0)1.69.15.73.53
> e-mail: marc.girondot at u-psud.fr
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> Skype: girondot
>
>